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Induction of CB2 receptor expression in the rat spinal cord of neuropathic but not inflammatory chronic pain models

2003· article· en· W2045531190 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Journal of Neuroscience · 2003
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsAstraZeneca (Canada)
Fundersnot available
KeywordsNeuropathic painChronic painMedicineSpinal cordCannabinoid receptor type 2MicrogliaReceptorNociceptionInflammationAnalgesicPharmacologyNeuroscienceImmune systemCannabinoid receptorImmunologyBiologyInternal medicineAgonistPhysical therapy

Abstract

fetched live from OpenAlex

Cannabinoids have been considered for some time as potent therapeutic agents in chronic pain management. Central and systemic administration of natural, synthetic and endogenous cannabinoids produce antinociceptive and antihyperalgesic effects in both acute and chronic animal pain models. Although much of the existing data suggest that the analgesic effects of cannabinoids are mediated via neuronal CB1 receptors, there is increasing evidence to support a role for peripheral CB2 receptors, which are expressed preferentially on immune cells. As yet, little is known about the central contribution of CB2 in neuropathic pain states. We report here that chronic pain models associated with peripheral nerve injury, but not peripheral inflammation, induce CB2 receptor expression in a highly restricted and specific manner within the lumbar spinal cord. Moreover, the appearance of CB2 expression coincides with the appearance of activated microglia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score0.308

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.052
GPT teacher head0.299
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it